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Abstract Details
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Activity Number:
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389
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Type:
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Invited
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Date/Time:
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Tuesday, August 2, 2011 : 2:00 PM to 3:50 PM
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Sponsor:
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IMS
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| Abstract - #300173 |
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Title:
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Gene-Set Analyses for Genome-Wide Association Studies (GWAS) Using Gene Ontology
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Author(s):
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Daniel J. Schaid*+
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Companies:
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Mayo Clinic
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Address:
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Division of Biomedical Statistics and Informatics, Rochester, 55905, USA
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Keywords:
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Gene Ontology ;
Gene Sets ;
Genome Wide Association ;
Score Statistics
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Abstract:
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Genome wide association studies (GWAS) measure hundreds of thousands of genetic markers (single nucleotide polymorphisms, SNPs) on large numbers of diseased cases and non-diseased controls, with most results reported according to the association of single SNPs with disease status. Although most studies find small odds ratios ranging 1.25 - 1.5 for SNPs, the benefit of GWAS can be enhanced by using prior information about how genes work together in biological pathways to create sets of genes. This presentation will discuss general strategies for scoring SNPs, combining these scores into gene-level scores, and then combining across genes in the same set. We use the publically available Gene Ontology to recursively create gene sets, capitalizing on its directed acyclic graph structure. Strengths and limitations of our approach will be discussed, as well as future research directions.
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